# coding: utf-8
import base64
import cv2
import numpy as np
from keras import models


from verify.utils import pretreatment
from verify.utils.mlearn_for_image import preprocess_input

TEXT_MODEL = ""
IMG_MODEL = ""


def get_text(img, offset=0):
    text = pretreatment.get_text(img, offset)
    text = cv2.cvtColor(text, cv2.COLOR_BGR2GRAY)
    text = text / 255.0
    h, w = text.shape
    text.shape = (1, h, w, 1)
    return text


def base64_to_image(base64_code):
    # base64解码
    img_data = base64.b64decode(base64_code)
    # 转换为np数组
    img_array = np.fromstring(img_data, np.uint8)
    # 转换成opencv可用格式
    img = cv2.imdecode(img_array, cv2.COLOR_RGB2BGR)

    return img


if __name__ == '__main__':
    pass
    # v = Verify()
    # v.verify("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")
    # verify("verify-img1.jpeg")
